Effects of Natural Organic Matter on the Dissolution Kinetics and Bioavailability of Metal Oxide Nanoparticles

The rapid development of nanotechnology and wider applications of engineered nanomaterials (ENMs) in the last few decades have generated concerns regarding their environmental and health risks. After release into the environment, ENMs undergo aggregation, transformation, and, for metal-based nanomaterials, dissolution processes, which together determine their fate, bioavailability and toxicity to living organisms in the ecosystems. The rates of these processes are dependent on nanomaterial characteristics as well as complex environmental factors, including natural organic matter (NOM). As a ubiquitous component of aquatic systems, NOM plays a key role in the aggregation, dissolution and transformation of metal-based nanomaterials and colloids in aquatic environments.

The goal of this dissertation work is to investigate how NOM fractions with different chemical and molecular properties affect the dissolution kinetics of metal oxide ENMs, such as zinc oxide (ZnO) and copper oxide (CuO) nanoparticles (NPs), and consequently their bioavailability to aquatic vertebrate, with Gulf killifish (Fundulus grandis) embryos as model organisms.

ZnO NPs are known to dissolve at relatively fast rates, and the rate of dissolution is influenced by water chemistry, including the presence of Zn-chelating ligands. A challenge, however, remains in quantifying the dissolution of ZnO NPs, particularly for time scales that are short enough to determine rates. This dissertation assessed the application of anodic stripping voltammetry (ASV) with a hanging mercury drop electrode to directly measure the concentration of dissolved Zn in ZnO NP suspensions, without separation of the ZnO NPs from the aqueous phase. Dissolved zinc concentration measured by ASV ([Zn]ASV) was compared with that measured by inductively coupled plasma mass spectrometry (ICP-MS) after ultracentrifugation ([Zn]ICP-MS), for four types of ZnO NPs with different coatings and primary particle diameters. For small ZnO NPs (4-5 nm), [Zn]ASV was 20% higher than [Zn]ICP-MS, suggesting that these small NPs contributed to the voltammetric measurement. For larger ZnO NPs (approximately 20 nm), [Zn]ASV was (79±19)% of [Zn]ICP-MS, despite the high concentrations of ZnO NPs in suspension, suggesting that ASV can be used to accurately measure the dissolution kinetics of ZnO NPs of this primary particle size.

Using the ASV technique to directly measure dissolved zinc concentration, we examined the effects of 16 different NOM isolates on the dissolution kinetics of ZnO NPs in buffered potassium chloride solution. The observed dissolution rate constants (kobs) and dissolved zinc concentrations at equilibrium increased linearly with NOM concentration (from 0 to 40 mg-C L-1) for Suwannee River humic acid (SRHA), Suwannee River fulvic acid and Pony Lake fulvic acid. When dissolution rates were compared for the 16 NOM isolates, kobs was positively correlated with certain properties of NOM, including specific ultraviolet absorbance (SUVA), aromatic and carbonyl carbon contents, and molecular weight. Dissolution rate constants were negatively correlated to hydrogen/carbon ratio and aliphatic carbon content. The observed correlations indicate that aromatic carbon content is a key factor in determining the rate of NOM-promoted dissolution of ZnO NPs. NOM isolates with higher SUVA were also more effective at enhancing the colloidal stability of the NPs; however, the NOM-promoted dissolution was likely due to enhanced interactions between surface metal ions and NOM rather than smaller aggregate size.

Based on the above results, we designed experiments to quantitatively link the dissolution kinetics and bioavailability of CuO NPs to Gulf killifish embryos under the influence of NOM. The CuO NPs dissolved to varying degrees and at different rates in diluted 5‰ artificial seawater buffered to different pH (6.3-7.5), with or without selected NOM isolates at various concentrations (0.1-10 mg-C L-1). NOM isolates with higher SUVA and aromatic carbon content (such as SRHA) were more effective at promoting the dissolution of CuO NPs, as with ZnO NPs, especially at higher NOM concentrations. On the other hand, the presence of NOM decreased the bioavailability of dissolved Cu ions, with the uptake rate constant negatively correlated to dissolved organic carbon concentration ([DOC]) multiplied by SUVA, a combined parameter indicative of aromatic carbon concentration in the media. When the embryos were exposed to CuO NP suspension, changes in their Cu content were due to the uptake of both dissolved Cu ions and nanoparticulate CuO. The uptake rate constant of nanoparticulate CuO was also negatively correlated to [DOC]×SUVA, in a fashion roughly proportional to changes in dissolved Cu uptake rate constant. Thus, the ratio of uptake rate constants from dissolved Cu and nanoparticulate CuO (ranging from 12 to 22, on average 17±4) were insensitive to NOM type or concentration. Instead, the relative contributions of these two Cu forms were largely determined by the percentage of CuO NP that was dissolved.

Overall, this dissertation elucidated the important role that dissolved NOM plays in affecting the environmental fate and bioavailability of soluble metal-based nanomaterials. This dissertation work identified aromatic carbon content and its indicator SUVA as key NOM properties that influence the dissolution, aggregation and biouptake kinetics of metal oxide NPs and highlighted dissolution rate as a useful functional assay for assessing the relative contributions of dissolved and nanoparticulate forms to metal bioavailability. Findings of this dissertation work will be helpful for predicting the environmental risks of engineered nanomaterials.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Catalytic decomposition of formic acid using supported metal nanoparticles

Upgrade of hydrogen to valuable fuel is a central topic in modern research due to its high availability and low price. For the difficulties in hydrogen storage, different pathways are still under investigation. A promising way is in the liquid-phase chemical hydrogen storage materials, because they can lead to greener transformation processes with the on line development of hydrogen for fuel cells. The aim of my work was the optimization of catalysts for the decomposition of formic acid made by sol immobilisation method (a typical colloidal method). Formic acid was selected because of the following features: it is a versatile renewable reagent for green synthesis studies. The first aim of my research was the synthesis and optimisation of Pd nanoparticles by sol-immobilisation to achieve better catalytic performances and investigate the effect of particle size, oxidation state, role of stabiliser and nature of the support. Palladium was chosen because it is a well-known active metal for the catalytic decomposition of formic acid. Noble metal nanoparticles of palladium were immobilized on carbon charcoal and on titania. In the second part the catalytic performance of the “homemade” catalyst Pd/C to a commercial Pd/C and the effect of different monometallic and bimetallic systems (AuxPdy) in the catalytic formic acid decomposition was investigated. The training period for the production of this work was carried out at the University of Cardiff (Group of Dr. N. Dimitratos).

Mixing performance evaluation of additive manufactured milli-scale reactors

The mixing performance of three passive milli-scale reactors with different geometries was investigated at different Reynolds numbers. The effects of design and operating characteristics such as mixing channel shape and volume flow rate were investigated. The main objective of this work was to demonstrate a process design method that uses on Computational Fluid Dynamics (CFD) for modeling and Additive Manufacturing (AM) technology for manufacture. The reactors were designed and simulated using SolidWorks and Fluent 15.0 software, respectively. Manufacturing of the devices was performed with an EOS M-series AM system. Step response experiments with distilled Millipore water and sodium hydroxide solution provided time-dependent concentration profiles. Villermaux-Dushman reaction experiments were also conducted for additional verification of CFD results and for mixing efficiency evaluation of the different geometries. Time-dependent concentration data and reaction evaluation showed that the performance of the AM-manufactured reactors matched the CFD results reasonably well. The proposed design method allows the implementation of new and innovative solutions, especially in the process design phase, for industrial scale reactor technologies. In addition, rapid implementation is another advantage due to the virtual flow design and due to the fast manufacturing which uses the same geometric file formats.

Recuperação de componentes de metal duro por projeção térmica

The main objective of this work is the development of a hardmetal components (WC-6%Co) recovery method by thermal deposition process. The thermal deposition technique used was HVOF (high velocity oxygen-fuel). The HVOF enables depositions of thick coatings (100-500 µm) with low porosity levels, high hardness and excellent adhesion. Before deposition, hardmetal samples with different geometries (plates and cylinders) were finished in order to have different roughness. The influence of these parameters in adhesion was studied. After this step, different re-sintering temperatures were used, in order to determine which one allows to obtain the maxima densification, elements distribution and metallurgical bonding. The re-sintering promotes the densification of the coating, with an increase of its hardness and metallurgical bonding formation. The inclusion of an intermetallic layer was tested along with different layer parameters. In liquid phase sintering (1383 and 1455 ºC) a complete densification of the coating occurred, while a bonding between the substrate and the coating only partially happened. The results of SEM/EDS show low levels of porosity and a complete and uniform distribution of the elements of the alloy. The cylindrical samples without intermetallic layer showed the lowest level of porosity and best metallurgical bonding. When the substrate surface was polished (Ra = 0.05 mm) lower levels of porosity and greater metallurgical bonding were found for both geometries. Taking into account the results obtained in this study, we can conclude that the implementation of this process is appropriate for cylindrical components with a polished surface. In these components the intermetallic layer is unnecessary and punctual defects like pores can be repaired with this process.

Modeling of burden distribution in the blast furnace

The blast furnace is the main ironmaking production unit in the world which converts iron ore with coke and hot blast into liquid iron, hot metal, which is used for steelmaking. The furnace acts as a counter-current reactor charged with layers of raw material of very different gas permeability. The arrangement of these layers, or burden distribution, is the most important factor influencing the gas flow conditions inside the furnace, which dictate the efficiency of the heat transfer and reduction processes. For proper control the furnace operators should know the overall conditions in the furnace and be able to predict how control actions affect the state of the furnace. However, due to high temperatures and pressure, hostile atmosphere and mechanical wear it is very difficult to measure internal variables. Instead, the operators have to rely extensively on measurements obtained at the boundaries of the furnace and make their decisions on the basis of heuristic rules and results from mathematical models. It is particularly difficult to understand the distribution of the burden materials because of the complex behavior of the particulate materials during charging. The aim of this doctoral thesis is to clarify some aspects of burden distribution and to develop tools that can aid the decision-making process in the control of the burden and gas distribution in the blast furnace. A relatively simple mathematical model was created for simulation of the distribution of the burden material with a bell-less top charging system. The model developed is fast and it can therefore be used by the operators to gain understanding of the formation of layers for different charging programs. The results were verified by findings from charging experiments using a small-scale charging rig at the laboratory. A basic gas flow model was developed which utilized the results of the burden distribution model to estimate the gas permeability of the upper part of the blast furnace. This combined formulation for gas and burden distribution made it possible to implement a search for the best combination of charging parameters to achieve a target gas temperature distribution. As this mathematical task is discontinuous and non-differentiable, a genetic algorithm was applied to solve the optimization problem. It was demonstrated that the method was able to evolve optimal charging programs that fulfilled the target conditions. Even though the burden distribution model provides information about the layer structure, it neglects some effects which influence the results, such as mixed layer formation and coke collapse. A more accurate numerical method for studying particle mechanics, the Discrete Element Method (DEM), was used to study some aspects of the charging process more closely. Model charging programs were simulated using DEM and compared with the results from small-scale experiments. The mixed layer was defined and the voidage of mixed layers was estimated. The mixed layer was found to have about 12% less voidage than layers of the individual burden components. Finally, a model for predicting the extent of coke collapse when heavier pellets are charged over a layer of lighter coke particles was formulated based on slope stability theory, and was used to update the coke layer distribution after charging in the mathematical model. In designing this revision, results from DEM simulations and charging experiments for some charging programs were used. The findings from the coke collapse analysis can be used to design charging programs with more stable coke layers.

Investigating wetting characteristics on microstructured surfaces for superhydrophobicity and metal microcasting

The engineering of liquid behavior on surfaces is important for infrastructure, transportation, manufacturing, and sensing. Surfaces can be rendered superhydrophobic by microstructuring, and superhydrophobic devices could lead to practical corrosion inhibition, self-cleaning, fluid flow control, and surface drag reduction. To more fully understand how liquid interacts with microstructured surfaces, this dissertation introduces a direct method for determining droplet solid-liquid-vapor interfacial geometry on microstructured surfaces. The technique performs metrology on molten metal droplets deposited onto microstructured surfaces and then frozen. Unlike other techniques, this visualization technique can be used on large areas of curved and opaque microstructured surfaces to determine contact line. This dissertation also presents measurements and models for how curvature and flexing of microstructured polymers affects hydrophobicity. Increasing curvature of microstructured surfaces leads to decreased slide angle for liquid droplets suspended on the surface asperities. For a surface with regularly spaced asperities, as curvature becomes more positive, droplets suspended on the tops of asperities are suspended on fewer asperities. Curvature affects superhydrophobicity because microscopic curvature changes solid-liquid interaction, pitch is altered, and curvature changes the shape of the three phase contact line. This dissertation presents a model of droplet interactions with curved microstructured surfaces that can be used to design microstructure geometries that maintain the suspension of a droplet when curved surfaces are covered with microstructured polymers. Controlling droplet dynamics could improve microfluidic devices and the shedding of liquids from expensive equipment, preventing corrosion and detrimental performance. This dissertation demonstrates redirection of dynamic droplet spray with anisotropic microstructures. Superhydrophobic microstructured surfaces can be economically fabricated using metal embossing masters, so this dissertation describes casting-based microfabrication of metal microstructures and nanostructures. Low melting temperature metal was cast into flexible silicone molds which were themselves cast from microfabricated silicon templates. The flexibility of the silicone mold permits casting of curved surfaces, which this dissertation demonstrates by fabricating a cylindrical metal roller with microstructures. The metal microstructures can be in turn used as a reusable molding tool. This dissertation also describes an industrial investment casting process to produce aluminum molds having integrated microstructures. Unlike conventional micromolding tools, the aluminum mold was large and had complex curved surfaces. The aluminum was cast into curved microstructured ceramic molds which were themselves cast from curved microstructured rubber. Many structures were successfully cast into the aluminum with excellent replication fidelity, including circular, square, and triangular holes. This dissertation demonstrates molding of large, curved surfaces having surface microstructures using the aluminum mold. This work contributes a more full understanding of the phenomenon of superhydrophobicity and techniques for the economic fabrication of superhydrophobic microstructures.

Exploring coordination-driven self-assembly with autonomous chemical robots

The work presented herein focused on the automation of coordination-driven self assembly, exploring methods that allow syntheses to be followed more closely while forming new ligands, as part of the fundamental study of the digitization of chemical synthesis and discovery. Whilst the control and understanding of the principle of pre-organization and self-sorting under non-equilibrium conditions remains a key goal, a clear gap has been identified in the absence of approaches that can permit fast screening and real-time observation of the reaction process under different conditions. A firm emphasis was thus placed on the realization of an autonomous chemical robot, which can not only monitor and manipulate coordination chemistry in real-time, but can also allow the exploration of a large chemical parameter space defined by the ligand building blocks and the metal to coordinate. The self-assembly of imine ligands with copper and nickel cations has been studied in a multi-step approach using a self-built flow system capable of automatically controlling the liquid-handling and collecting data in real-time using a benchtop MS and NMR spectrometer. This study led to the identification of a transient Cu(I) species in situ which allows for the formation of dimeric and trimeric carbonato bridged Cu(II) assemblies. Furthermore, new Ni(II) complexes and more remarkably also a new binuclear Cu(I) complex, which usually requires long and laborious inert conditions, could be isolated. The study was then expanded to the autonomous optimization of the ligand synthesis by enabling feedback control on the chemical system via benchtop NMR. The synthesis of new polydentate ligands has emerged as a result of the study aiming to enhance the complexity of the chemical system to accelerate the discovery of new complexes. This type of ligand consists of 1-pyridinyl-4-imino-1,2,3-triazole units, which can coordinate with different metal salts. The studies to test for the CuAAC synthesis via microwave lead to the discovery of four new Cu complexes, one of them being a coordination polymer obtained from a solvent dependent crystallization technique. With the goal of easier integration into an automated system, copper tubing has been exploited as the chemical reactor for the synthesis of this ligand, as it efficiently enhances the rate of the triazole formation and consequently promotes the formation of the full ligand in high yields within two hours. Lastly, the digitization of coordination-driven self-assembly has been realized for the first time using an in-house autonomous chemical robot, herein named the ‘Finder’. The chemical parameter space to explore was defined by the selection of six variables, which consist of the ligand precursors necessary to form complex ligands (aldehydes, alkineamines and azides), of the metal salt solutions and of other reaction parameters – duration, temperature and reagent volumes. The platform was assembled using rounded bottom flasks, flow syringe pumps, copper tubing, as an active reactor, and in-line analytics – a pH meter probe, a UV-vis flow cell and a benchtop MS. The control over the system was then obtained with an algorithm capable of autonomously focusing the experiments on the most reactive region (by avoiding areas of low interest) of the chemical parameter space to explore. This study led to interesting observations, such as metal exchange phenomena, and also to the autonomous discovery of self assembled structures in solution and solid state – such as 1-pyridinyl-4-imino-1,2,3-triazole based Fe complexes and two helicates based on the same ligand coordination motif.

Swelling properties of alkali-metal doped polymeric anion-exchange membranes in alcohol media for application in fuel cells

Swelling properties of four commercial anion-exchange membranes with different structure have been analyzed in several hydro-organic media. With this target, the liquid uptake and the surface expansion of the membranes in contact with different pure liquids, water and alcohols (methanol, ethanol and 1-propanol), and with water alcohol mixtures with different concentrations have been experimentally determined in presence and in absence of an alkaline medium (LiOH, NaOH and KOH of different concentrations). The alkali-metal doping effect on the membrane water uptake has also been investigated, analyzing the influence of the hydroxide concentration and the presence of an alcohol in the doping solution. The results show that the membrane structure plays an essential role in the influence that alcohol nature and alkaline media has on the selective properties of the membrane. The heterogeneous membranes, with lower density, show higher liquid uptakes and dimensional changes than the homogeneous membranes, regardless of the doping conditions. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Pirólise rápida catalítica do capim elefante utilizando materiais mesoporosos e óxidos metálicos para deoxigenação em bio-óleo

The fast pyrolysis of lignocellulosic biomass is a thermochemical conversion process for production energy which have been very atratactive due to energetic use of its products: gas (CO, CO2, H2, CH4, etc.), liquid (bio-oil) and charcoal. The bio-oil is the main product of fast pyrolysis, and its final composition and characteristics is intrinsically related to quality of biomass (ash disposal, moisture, content of cellulose, hemicellulose and lignin) and efficiency removal of oxygen compounds that cause undesirable features such as increased viscosity, instability, corrosiveness and low calorific value. The oxygenates are originated in the conventional process of biomass pyrolysis, where the use of solid catalysts allows minimization of these products by improving the bio-oil quality. The present study aims to evaluate the products of catalytic pyrolysis of elephant grass (Pennisetum purpureum Schum) using solid catalysts as tungsten oxides, supported or not in mesoporous materials like MCM-41, derived silica from rice husk ash, aimed to reduce oxygenates produced in pyrolysis. The biomasss treatment by washing with heated water (CEL) or washing with acid solution (CELix) and application of tungsten catalysts on vapors from the pyrolysis process was designed to improve the pyrolysis products quality. Conventional and catalytic pyrolysis of biomass was performed in a micro-pyrolyzer, Py-5200, coupled to GC/MS. The synthesized catalysts were characterized by X ray diffraction, infrared spectroscopy, X ray fluorescence, temperature programmed reduction and thermogravimetric analysis. Kinetic studies applying the Flynn and Wall model were performed in order to evaluate the apparent activation energy of holoceluloce thermal decomposition on samples elephant grass (CE, CEL and CELix). The results show the effectiveness of the treatment process, reducing the ash content, and were also observed decrease in the apparent activation energy of these samples. The catalytic pyrolysis process converted most of the oxygenate componds in aromatics such as benzene, toluene, ethylbenzene, etc

Site Specifc Growth of Metal Catalyzed Silica Nanowires for Biological and Chemical Sensing

In this research the integration of nanostructures and micro-scale devices was investigated using silica nanowires to develop a simple yet robust nanomanufacturing technique for improving the detection parameters of chemical and biological sensors. This has been achieved with the use of a dielectric barrier layer, to restrict nanowire growth to site-specific locations which has removed the need for post growth processing, by making it possible to place nanostructures on pre-pattern substrates. Nanowires were synthesized using the Vapor-Liquid-Solid growth method. Process parameters (temperature and time) and manufacturing aspects (structural integrity and biocompatibility) were investigated. Silica nanowires were observed experimentally to determine how their physical and chemical properties could be tuned for integration into existing sensing structures. Growth kinetic experiments performed using gold and palladium catalysts at 1050 ˚C for 60 minutes in an open-tube furnace yielded dense and consistent silica nanowire growth. This consistent growth led to the development of growth model fitting, through use of the Maximum Likelihood Estimation (MLE) and Bayesian hierarchical modeling. Transmission electron microscopy studies revealed the nanowires to be amorphous and X-ray diffraction confirmed the composition to be SiO2 . Silica nanowires were monitored in epithelial breast cancer media using Impedance spectroscopy, to test biocompatibility, due to potential in vivo use as a diagnostic aid. It was found that palladium catalyzed silica nanowires were toxic to breast cancer cells, however, nanowires were inert at 1µg/mL concentrations. Additionally a method for direct nanowire integration was developed that allowed for silica nanowires to be grown directly into interdigitated sensing structures. This technique eliminates the need for physical nanowire transfer thus preserving nanowire structure and performance integrity and further reduces fabrication cost. Successful nanowire integration was physically verified using Scanning electron microscopy and confirmed electrically using Electrochemical Impedance Spectroscopy of immobilized Prostate Specific Antigens (PSA). The experiments performed above serve as a guideline to addressing the metallurgic challenges in nanoscale integration of materials with varying composition and to understanding the effects of nanomaterials on biological structures that come in contact with the human body.

Impact of potassium and phosphorus in biomass on the properties of fast Pyrolysis bio-oil

This study investigates fast pyrolysis bio-oils produced from alkali-metal-impregnated biomass (beech wood). The impregnation aim is to study the catalytic cracking of the pyrolysis vapors as a result of potassium or phosphorus. It is recognized that potassium and phosphorus in biomass can have a major impact on the thermal conversion processes. When biomass is pyrolyzed in the presence of alkali metal cations, catalytic cracking of the pyrolysis liquids occurs in the vapor phase, reducing the organic liquids produced and increasing yields of water, char, and gas, resulting in a bio-oil that has a lower calorific value and an increased chance of phase separation. Beech wood was impregnated with potassium or phosphorus (K impregnation and P impregnation, respectively) in the range of 0.10-2.00 wt %. Analytical pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) was used to examine the pyrolysis products during thermal degradation, and thermogravimetric analysis (TGA) was used to examine the distribution of char and volatiles. Both potassium and phosphorus are seen to catalyze the pyrolytic decomposition of biomass and modify the yields of products. 3-Furaldehyde and levoglucosenone become more dominant products upon P impregnation, pointing to rearrangement and dehydration routes during the pyrolysis process. Potassium has a significant influence on cellulose and hemicellulose decomposition, not just on the formation of levoglucosan but also other species, such as 2(5H)-furanone or hydroxymethyl-cyclopentene derivatives. Fast pyrolysis processing has also been undertaken using a laboratory-scale continuously fed bubbling fluidized-bed reactor with a nominal capacity of 1 kg h-1 at the reaction temperature of 525 °C. An increase in the viscosity of the bio-oil during the stability assessment tests was observed with an increasing percentage of impregnation for both additives. This is because bio-oil undergoes polymerization while placed in storage as a result of the inorganic content. The majority of inorganics are concentrated in the char, but small amounts are entrained in the pyrolysis vapors and, therefore, end up in the bio-oil.

Biological Approaches for Remediation of Metal-Contaminated Sites

Environmental pollution by several heavy metals and metalloids is a severe problem worldwide, as soils became increasingly contaminated, posing a threat to ecosystems and ultimately to human health. Contamination derives from large scale urbanization and industrialization, threatening land ecosystems, surface and groundwater, as well as food safety and human health. Remediation strategies for heavy metal-contaminated sites are necessary to protect from their toxic effects and conserve the environment for future generations. Numerous physicochemical techniques have been adopted including excavation and deposition in landfills, thermal treatment, leaching and electro-reclamation. These techniques are fast but inadequate, costly, cause adverse effects on soil physical, chemical and biological properties, and may lead to secondary pollution. In fact, many of these approaches only change the problem from one form or place to another, and do not completely destroy the pollutants. There was an urgent need to develop new technologies which are cost-effective and eco-friendly. In this context, biological remediation has tremendous potential. It uses plants and microorganisms to remove or contain toxic contaminants and is considered as the most effective method because it is a natural process, environmentally-friendly, has a low cost, and wide public acceptance. The present chapter aims to provide a comprehensive review of some of the promising processes mediated by plant and microbes to remediate metal-contaminated environments. Some biological processes used for the decontamination of organic compounds will also be included because of their relevance and potential common use for both purposes.